People often ask me about what kind of problems best leverage the benefits of a collective intelligence (CI) approach. I always say it depends on several factors, but according to my experience I think I am able to advance here seven types of problems or challenges that that can be suitable for open and participatory project with good results:

• Creativity: CI is quite effective at generating ideas. The more people thinking, the more likely they will find a creative solution.

• Bias assessment: Activities those are highly susceptible to selection and assessment biases due to their inherent relativity or spurious interests. CI works well in data interpretation tasks subject to many different perspectives. Opening the analysis to a wide variety of points of view can help reduce the “expert bias” and achieve a more complete and balanced judgment.

• Distributed Surveillance: Activities in which the cost of failure is high. Any errors are best detected if more people are reviewing (Remember Linus’s Law enunciated ​​by Eric Raymond: “Given enough eyeballs, all bugs are shallow“).

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Nature can inspire us to explore emerging models of interaction that will help to better understand patterns of collective intelligence in human groups. Steven Johnson, in his book “Emerging Systems” (2001), masterfully demonstrates how that connection (called Biomimicry or biomimetics) is full of metaphors. The Web Ask Nature, the Biomimicry Institute, brings together hundreds of examples of such associations.

In a previous post I mentioned that one of the things I liked about the Collective Intelligence Conference held at MIT in April 2012 was to listen to Deborah Gordon (Stanford) and Ian Couzin (Princeton), two behavioral biologists, who focused on the study of the patterns of behavior of animals in their natural habitats. They are not “biologists” in its classical sense but work as multidisciplinary groups that are making increasing use of mathematics and computer science as well as tracking and geolocation devices to investigate the collective behavior of swarms or “Swarm Intelligence“, a branch of artificial intelligence based on the collective behavior of decentralized and self-organized systems. Read more ›